Diagnosing pathologies of the eye often involves examination of ocular fundus images. For example, in US PGPUB 2007/0002275, Yan et al. describe a method and system for the automatic detection of microaneursms in such images. More generally, these images can be used to diagnose a variety of conditions, for example from a review of differences in such images taken over a period of time.
Automated detection of differences between ocular fundus images requires an understanding of purportedly normal conditions and, inasmuch as it is difficult to determine such conditions, often produces less than satisfactory results. At the same time, manual screening of such images is a time-consuming and operator-dependent process. That is, the results of manual screening are often solely depend on the skill of the observer who is expected to make meaningful comparisons of images captured at different times in different conditions. Inevitably, some misdiagnoses are made.